Introduction
How humanitarians estimate travel time
Travel time is a more prominent indicator now due to JIAF
Travel time is one small component of service access
Advances in health facility data, DTM and OSM
Computational approaches to service access
Building upon previous work with Manon
Objectives
- Compare service access measurement via KI and computational approaches
- Utilize computational approaches to quality check key informant data.
- Identify priority locations to investigate barriers other than travel time
- Reproducible approach that can be systematized
Methodology
- Overview of sites, facilities and combined
- Focus on 1 country Mozambique
- Get IDP location data, health facility data
Analysis
Mandruzi IDP site
Map of IDP site, health sites and route to nearest facility. Comparing to KI
Spatial distribution of IDP sites and Health Facilities
Browse all IDP sites, health facilities and routes to the nearest health facility
Distribution of computed travel times
histogram of computed times…
histogram of KI times…
Comparison against KI responses
.. how many sites have different computed times to KI times?
Patterns of variance
.. what are the potential explanations as to why this variance exists?
QC - enumerators
… do some enumerators have more responses that differ from the computed travel time than others? (flagging potential issues for better training or quality control)
Spatial patterns
is there any spatial clustering of sites with a mismatch? This could be a flag to highlight areas where barriers other than travel time maybe be a key factor list of sites to further examine barriers
Findings
Ask travel time in minutes, with inclusion of mode. Check for patterns by KI which may indicate QC issues.
Limitations & next steps
Road networks Types Elevation Systematizing